Abstract

References (54)

Using the URL or DOI link below will
ensure access to this page indefinitely

Based on your IP address, your paper is being delivered by:

New York, USA

Processing request.

Illinois, USA

Processing request.

Brussels, Belgium

Processing request.

Seoul, Korea

Processing request.

California, USA

Processing request.

If you have any problems downloading this paper,please click on another Download Location above, or view our FAQFile name: SSRN-id2539662. ; Size: 607K

You will receive a perfect bound, 8.5 x 11 inch, black and white printed copy of this PDF document with a glossy color cover. Currently shipping to U.S. addresses only. Your order will ship within 3 business days. For more details, view our FAQ.

Quantity:Total Price = $9.99 plus shipping (U.S. Only)

If you have any problems with this purchase, please contact us for assistance by email: Support@SSRN.com or by phone: 877-SSRNHelp (877 777 6435) in the United States, or +1 585 442 8170 outside of the United States. We are open Monday through Friday between the hours of 8:30AM and 6:00PM, United States Eastern.

Abandonment in queues has long been recognized as having a significant impact on system performance. Yet, our empirical understanding of the key drivers for abandonment, particularly in observable systems, is limited. Furthermore, most models of abandonment assume that it occurs after a length of time sampled from an exogenous distribution, with no dependence on the system. However, discrete-event simulation, a commonly used tool for decision making in service systems, permits much more complex (and hence accurate) models of abandonment than those simply based on time in system. This paper studies three key drivers of abandonment, namely, waiting time, queue-length, and service rate, which are also tractable for modeling. Using operational data from a hospital emergency department, we show that all three factors affect a patient’s propensity for leaving the waiting area without being seen by a physician (LWBS). Further, these factors interact with each other in a non-linear fashion. We also examine the shape of the hazard rate curves for LWBS behavior and find that an exponential distribution, as is commonly assumed for abandonment, is likely not a good model for such systems. We use these findings to make recommendations for simulating LWBS behavior. Further, we discuss the state-of-the art for existing queueing models of abandonment and translate how our findings affect the utility of these models. The results point to the need for further queueing model development.